Job DescriptionPurpose of the Role

NThe Azure Data & Integration Architect will lead enterprise-wide data and integration initiatives, leveraging Microsoft Azure and Databricks to drive digital transformation, operational efficiency, and data-driven decision-making. This role focuses on architecting scalable data pipelines, designing a unified lakehouse platform, enabling advanced analytics, and integrating enterprise systems across SAP and non-SAP landscapes.

NKey Responsibilities

nData Architecture & Analytics

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- Implement Unity Catalog for governance, data lineage, and access control.
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- Design and deploy enterprise data models and analytical layers using Azure.
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- Enable enterprise reporting and self-service analytics through Power BI integration.
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- Manage both structured and unstructured data using Azure Blob Storage and Azure Data Lake Storage Gen2.
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- Collaborate with data scientists and business teams to enable machine learning and predictive analytics use cases.
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- Define and enforce dataarchitecture standards, naming conventions, and performance best practices.
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nIntegration & Enterprise Connectivity

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- Design and implement integrations between SAP and non-SAP systems using SAP CPI, Azure API Management, and REST/SOAP APIs.
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- Ensure secure and scalable data flow across on-premises, cloud, and hybrid environments.
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- Implement API authentication and security protocols (OAuth 2.0, JWT, SAML).
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- Integrate enterprise applications with Azure Entra ID for identity and access management.
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- Establish reusable integration patterns and frameworks for enterprise-wide adoption.
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nGovernance, Security & Compliance

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- Ensure data quality, lineage, and governance across the analytics ecosystem.
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- Implement security and compliance controls aligned with GxP, 21 CFR Part 11, and corporate IT policies.
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- Monitor cost and performance optimization across Azure services.
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- Oversee DevOps and CI/CD pipelines for automated deployment and testing using Azure DevOps.
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nLeadership & Collaboration

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- Collaborate closely with cross-functional IT, data, and business teams.
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- Conduct technical design reviews, mentor developers, and ensure adherence to architectural standards.
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- Support vendor evaluations, solution assessments, and proof-of-concept initiatives.
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- Communicate complex technical concepts effectively to senior management and business stakeholders.
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nEducation & Qualifications

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- Bachelors or Masters degree in Computer Science, Information Technology, or related field.
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- MBA is a plus.
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NMandatory Requirements

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- Minimum 6+ years of experience in data analytics, engineering, and enterprise integration.
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- Proven experience architecting enterprise-scale data platforms on Azure.
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- Strong hands-on expertise in Azure Databricks (PySpark, Delta Lake, Unity Catalog).
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- Proficiency in Azure Data Factory, Azure Synapse Analytics, Power BI, Blob Storage, and Data Lake Gen2.
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- Experience integrating SAP systems (S/4HANA, SuccessFactors, MES, LIMS, CRM) with Azure and other platforms.
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- Proficient in integration technologies (SAP CPI, Azure API Management, middleware platforms).
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- Deep understanding of data security and identity protocols (OAuth, JWT, SAML) and Azure Entra ID.
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- Familiarity with GxP-compliant data handling and governance practices.
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- Strong proficiency in Python, PySpark, and SQL, hands on experience in writing clean, effective and scalable code
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nDesirable Requirements

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- Experience in pharmaceutical manufacturing and regulatory environments. Exposure to Azure DevOps, Terraform, or ARM templates for infrastructure automation.
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- Knowledge of modern data architecture principles (Lakehouse, Data Mesh, ELT).
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- Experience with AgenticAI, preferably using Microsoft AI technologies
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nPreferred Certifications

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- Microsoft Certified: Azure Solutions Architect Expert
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- Microsoft Certified: Data Engineer Associate
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- Microsoft Certified: Identity and Access Administrator Associate
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- Preferred Industry Experience
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- Pharmaceutical Manufacturing
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- Regulated Environments (GxP, FDA, ISO)
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📌 Data Engineering Lead (Karnataka)
🏢 BIOCON BIOLOGICS
📍 Karnataka